Administration & Service occupation
Will AI replace Data Entry Worker?
See how this occupation’s day-to-day work compares with other jobs in exposure to AI and automation, why it received this result, and where human skills remain essential.
Data Entry Worker
Data Entry Keyers · Administration & Service
This job is near the higher end of our AI & automation comparison.
Exposure index: 99 / 100
This compares the type of work in this job with the work in hundreds of other jobs.
This is a comparison between jobs — not a 99% chance of job loss.
Why did this job get this result?
- Typing alphanumeric data from paper records into computer databases involves nearly continuous computer keyboarding.
- Transcribing form fields, verifying data accuracy, and formatting entry sheets follow highly repetitive, standardized protocols.
- The occupation is conducted in quiet office or remote data processing centers with zero physical machinery automation.
- Keyers must verify illegible handwriting, identify obvious source data errors, and maintain strict data accuracy benchmarks.
- Communicating with supervisors to clarify missing source records involves basic operational coordination.
How technology may change this work
Technology and human strengths
What AI & automation may affect
- Optical character recognition (OCR) and automated document capture tools can extract text and numeric data from standard scanned documents.
- Automated database validation scripts and web forms capture customer and business data directly at the point of origin.
Human strengths in this job
- Deciphering severely degraded, ambiguous, or damaged historical records and handwriting that OCR software fails to read
- Verifying critical medical, legal, and financial records where data entry errors would cause severe real-world harm
- Flagging fraudulent, forged, or suspicious source documents during high-volume data intake processing
- Applying context-specific human judgment when source document fields do not conform to standardized data schemas
How this result breaks down
These are model components, not percentages of the job or of how necessary people are.
How much the job involves information, data, writing, analysis or other digital work that AI and software may help with.
How much of the work follows regular, predictable or repeated steps.
How much of the physical work may be suitable for machines or robotics.
How much the job depends on judgment, creativity, communication and adapting to real situations.
How is the index calculated?
The Exposure Index is a percentile comparing this job's digital, routine, and physical tasks against all 897 occupations in the Model 2.1 dataset. A score of 99 means higher modeled exposure than approximately 99% of comparable jobs.
Your work may differ
How does your work compare?
Two people with the same job title can do very different work. Answer seven quick questions to see how your specific day-to-day tasks compare.
What people in this job commonly do
- Locate and correct data entry errors, or report them to supervisors.
- Compile, sort, and verify the accuracy of data before it is entered.
- Compare data with source documents, or re-enter data in verification format to detect errors.
- Store completed documents in appropriate locations.
- Select materials needed to complete work assignments.
- Read source documents such as canceled checks, sales reports, or bills, and enter data in specific data fields or onto tapes or disks for subsequent entry, using keyboards or scanners.
How we compare jobs
We look at what people do in hundreds of occupations — including digital work, repeatable activities, physical automation and human skills — then compare the job with other occupations.
What this tool cannot predict
It cannot predict individual job loss, exact technology adoption timing or decisions by an individual employer.
Occupation and data details
O*NET-SOC: 43-9021.00
Career category: Administration & Service
Typical education: High school diploma or equivalent
Data source: O*NET, U.S. Department of Labor.
This product includes information from the O*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under the CC BY 4.0 license. Toolsyte has modified and scored some information; USDOL/ETA has not approved, endorsed, or tested these modifications. O*NET® is a trademark of USDOL/ETA.